Senior Data & Analytics Engineer

About the Company

At OneClick Code, we are revolutionizing the roofing and restoration industry through smart automation, data transparency, and instant access to critical building information. Our mission is to empower contractors, adjusters, and insurance professionals with accurate, jurisdiction-specific codes and permit data, instantly, so they can work smarter, not harder.

Founded in 2018, with a vision to eliminate the inefficiencies and guesswork that slow down claims and repairs, OneClick Code has become the go-to platform for accessing trusted roofing codes, manufacturer specifications, tax jurisdiction data, and permit requirements, all in just one click.

We're a fast-growing, venture-backed startup that thrives on innovation, collaboration, and impact. As we scale, we're looking for mission-driven team members who are passionate about using technology to bring clarity and confidence to an often-overlooked corner of the construction world.

The Opportunity

The Senior Data & Analytics Engineer will own the reliability and evolution of the company’s data and analytics infrastructure, including data models, the warehouse, pipelines, integrations, and billing data. This role moves beyond reporting into data modeling, analytics architecture, instrumentation strategy, and cross-functional enablement. The person will independently identify opportunities, translate ambiguous business needs into clear analytics initiatives, and drive those initiatives from definition through implementation and adoption.

This individual will serve as the technical bridge between raw data and business decision-making, leading the design of robust data models, optimizing SaaS metrics, and ensuring accurate tracking across web and native applications. Success in this role requires ownership of both technical quality and business outcomes.

This is a senior individual-contributor role. The person is expected to demonstrate leadership through initiative ownership, sound judgment, proactive communication, and cross-functional influence. People management is not currently a requirement.

Responsibilities

Analytics Architecture & Data Modeling

• Design, build, and maintain scalable analytics data models to support business reporting and decision-making.

• Build, maintain, and troubleshoot ETL/ELT pipelines and data transformations.

• Own source-of-truth definitions and reconcile data across application, billing, and analytics systems.

•

• Own the structure and optimization of SaaS metrics, including subscription lifecycle, billing, churn, retention, LTV, and revenue analytics (Stripe).

• Ensure data integrity, consistency, and governance across systems.

• Monitor data flows and proactively detect, troubleshoot, and recover from pipeline failures or missing data.

• Partner with Engineering to assess the data impact of product releases and prevent breaking changes to collection systems.

Instrumentation & Event Tracking

• Define tracking specifications and lead the auditing and validation of event strategy across web and native applications in partnership with Engineering.

• Partner with engineering and product teams to define, implement, and audit tracking standards.

• Improve reliability and completeness of user event data (Segment, Mixpanel, or similar tools).

Data Analysis & Insights

• Perform advanced analysis using SQL and Python to generate actionable insights.

• Identify trends, risks, and growth opportunities within SaaS performance metrics.

• Translate complex datasets into clear business recommendations for leadership.

Analytics Platform Ownership

• Build and continuously improve the company’s analytics framework and reporting ecosystem.

• Develop dashboards and data visualization assets that provide reliable, self-serve insights for stakeholders.

• Optimize data pipelines and queries for performance and scalability.

Cross-Functional Collaboration

• Lead cross-functional analytics initiatives by aligning Product,…